Notes

Ingeniería de Seguridad en Google: Mis Notas de Estudio para la Entrevista Por nolang Soy ingeniero de seguridad en Google y estas son las notas que tomé mientras estudiaba para las entrevistas. Este es mi primer trabajo en seguridad y mucha gente me ha preguntado cómo estudié. Mis notas consiste...

CVE-2026-41940

CVE-2026-41940 ✅ تحليل السكربت ما يفعله الماسح الضوئي وكيف ✅ شرح تقني للسبب الجذري فرق CRLF/Session.pm ✅ الوقاية — أوامر التصحيح، دروس البرمجة الآمنة ✅ التخفيف — قواعد جدار الحماية، إعداد WAF، التحصين ✅ البحث عن مؤشرات الاختراق — اكتشاف ما إذا كنت قد تعرضت للهجوم بالفعل ✅ منهجية VaPT — تحديد...

CVE-2021-44228---Log4Shell-Analysis

🔥 Log4Shell CVE-2021-44228 Analysis A comprehensive technical analysis of the Log4Shell vulnerability CVE-2021-44228, one of the most critical vulnerabilities in modern software history. 📖 Overview This repository contains an in-depth analysis of the Log4Shell vulnerability in Apache Log4j2,...

Follina-Vulnerability-CVE-2022-30190-Exploit-Analysis

Follina-Vulnerability-CVE-2022-30190-Exploit-Analysis Exploración de la vulnerabilidad Follina CVE-2022-30190 de Microsoft Office, que incluye un análisis detallado, explotación de prueba de concepto en un laboratorio controlado y estrategias de mitigación. Solo con fines educativos y de...

Exploit for Observable Discrepancy in Intel Atom_C

🛡️ Spectre Variant 2 CVE-2017-5715 — Hardware Vulnerability...

Catan and Mouse

Welcome to this week's edition of the Threat Source newsletter. " I do not know everything; still many things I understand." ― Madeleine L'Engle, A Wrinkle in Time " Don't try to comprehend with your mind. Your minds are very limited. Use your intuition." ― Madeleine L'Engle, A Wind in the Door T...

MAL-2026-5783 Malicious code in vault-strategies (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 6b7037d9efc65a0885cc000a92c46ea9bed2097d02c8fb2883ceaa3eb2fd5eeb On npm install, the package's preinstall hook preinstall: node postinstall.js || true executes postinstall.js, which enumerates process.env and filte...

Malicious code in vault-strategies (npm)

--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 6b7037d9efc65a0885cc000a92c46ea9bed2097d02c8fb2883ceaa3eb2fd5eeb On npm install, the package's preinstall hook preinstall: node postinstall.js || true executes postinstall.js, which enumerates process.env and filte...

wannacry-soc-lab

WannaCry SOC Investigation Lab Overview This project simu...

Evaluating and Combating the Impact of Concept Drift on the Performance of Machine Learning-Based Phishing Detection Systems

The expansion of the digital domain has resulted in a substantial increase in digital communication, with email emerging as one of the most prominent channels. The proliferation of email communication is apparent in both professional and personal contexts, thereby creating numerous vulnerabilitie...

When Discovery Outpaces Remediation: Modeling AI-Accelerated Vulnerability Discovery in Interconnected Systems

Advanced AI systems for code analysis, binary analysis, fuzzing orchestration, and penetration-test planningmay significantly increase the rate at which latent vulnerabilities are discovered. While improved discovery can benefit defenders, it can also overload remediation pipelines and accelerate...

Unveiling Privacy Risks in Multi-Modal Large Language Models: Task-Specific Vulnerabilities and Mitigation Challenges

Privacy risks in text-only Large Language Models LLMs are well studied, particularly their tendency to memorize and leak sensitive information. However, Multi-modal Large Language Models MLLMs, which process both text and images, introduce unique privacy challenges that remain underexplored...

Steganography without Modification: Hidden Communication Via LLM Seeds

We demonstrate that widely deployed Large Language Model LLM inference stacks harbor a steganographic channel that requires no modification to model weights, sampling code, or output distributions. The channel exploits a structural property of deterministic decoding: pseudo-random number generato...

CVE-2025-40904

A Stored HTML Injection vulnerability was discovered in the Smart Polling functionality due to improper validation of an input parameter. An authenticated user with limited privileges can push malicious remote strategies containing HTML tags through the sync. When a victim views the affected remo...

Beyond Pass/Fail: Using Process Mining to Understand How LLMs Resist (And Fail) Red Team Attacks

Standard AI red teaming evaluations reduce adversarial campaigns to a single binary outcome, attack success rate ASR, not taking into account the sequential structure of how models resist or yield to attacks. We propose applying process mining, a discipline for discovering and analyzing process...

Steering LLM Viewpoints through Fabricated Evidence Injection

As chatbots increasingly influence daily decision-making, their potential to produce misleading responses poses substantial risks to users. This paper investigates a critical cognitive vulnerability in LLMs: their tendency to uncritically trust external context when presented with fabricated...

Credential Disclosure in (EU) Digital Identity Wallets: Privacy Risks and Practical Mitigations

The European Union will introduce the EUDI Wallet by late 2026, which allows users to hold digital credentials i.e., representations of physical official identity documents on their devices. This will allow users to securely and privately disclose identity attributes to websites. Although such a...

TeleHunt: A Framework and Tool for Efficient Cybercriminal Community Discovery on Telegram

This paper presents TeleHunt, a framework and tool for evaluating the effectiveness of different strategies to discover cybercriminal communities on Telegram. TeleHunt employs a set of reference-driven snowballing strategies, integrating message-level classification, contextual filtering, and...

Description-Code Inconsistency in Real-World MCP Servers: Measurement, Detection, and Security Implications

The Model Context Protocol MCP has emerged as a critical standard empowering Large Language Models LLMs to utilize external tools. In this ecosystem, LLMs rely on natural language descriptions provided by MCP servers to select and execute functions. This interaction implicitly assumes that tool...

Quality-Diversity Evolution for Discovering Diverse Vulnerabilities in LLM Safety

Current approaches to LLM adversarial testing suffer from coverage gaps: manual red-teaming does not scale, LLM-as-attacker methods exhibit mode collapse, and gradient-based approaches produce uninterpretable gibberish. We introduce a quality-diversity evolutionary framework that operates at the...